1:Monday, 2:Tuesday, 3:Wednesday, 4:Thursday, 5:Friday, 6:Saturday, 7:Sunday
Since the p-value for gender and age are small, so the test is significant that gender and age are significantly effect the amount of salary.
Call:
lm(formula = amount ~ gender + age + Weekday, data = data1)
Residuals:
Min 1Q Median 3Q Max
-1361.6 -756.4 -204.2 480.0 6858.2
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2085.767 130.966 15.926 < 2e-16 ***
genderM 426.652 75.626 5.642 2.27e-08 ***
age -13.657 3.087 -4.424 1.09e-05 ***
Weekday 11.595 25.601 0.453 0.651
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1121 on 879 degrees of freedom
Multiple R-squared: 0.05394, Adjusted R-squared: 0.05071
F-statistic: 16.71 on 3 and 879 DF, p-value: 1.461e-10
Shapiro-Wilk normality test
data: res
W = 0.85767, p-value < 2.2e-16
The residuals were uncorrelated but not normally distributed. The modification of model is needed.